1. Field of the Invention
The present invention relates to an information processing apparatus and an information processing method, and a program thereof, and more particularly, to an information processing apparatus and an information processing method, and a program thereof which are capable of presenting details of preferences of other users in an easily recognized manner.
2. Description of the Related Art
As a method for retrieving and recommending a variety of items such as television programs, music, commercial products or the like on the basis of preferences of users, there is a collaborative filtering method based on evaluations of users.
In the collaborative filtering method, for example, there is a method that similar users (other users) who have evaluated the same items are selected on the basis of evaluation values of users for items, and other items selected by the similar users are recommended (P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl. “GroupLens: Open Architecture for Collaborative Filtering of Netnews,” Conference on Computer Supported Cooperative Work, pp. 175-186, 1994, and Hofmann, T., “Latent Semantic Models for Collaborative Filtering”, ACM Transactions on Information Systems, Vol. 22, No. 1, pp. 89-115, 2004.).
Meanwhile, there is a method that an evaluation method of the present user for items and evaluation methods of other users are presented as space distribution, and then, the evaluation method of the present user and the evaluation methods of the other users can be compared with each other (Japanese Patent Application Laid-open No. 2008-217311 and Japanese Patent Application Laid-open No. 2008-217312).
Further, there is a technology in which sentences on web pages are analyzed to present users having similar value standards.
However, in the above described methods, it is difficult to present details of preferences of other users in an easily recognized manner.
In the method disclosed in the P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl. “GroupLens: Open Architecture for Collaborative Filtering of Netnews.” Conference on Computer Supported Cooperative Work, pp. 175-186, 1994, since the level of similarity is calculated only for users who have evaluated the same items, it is difficult to recognize how other items are evaluated with respect to other users who have evaluated the other items.
In the method disclosed in the Hofmann, T. “Latent Semantic Models for Collaborative Filtering”, ACM Transactions on Information Systems, Vol. 22, No. 1, pp. 89-115, 2004, since it is not considered what kind of characteristics the items evaluated by users have, and since recommended items are limited to items which have been directly evaluated by other users, it is difficult to recommend items which are not evaluated by anybody. Further, since evaluation values based on a five-stage evaluation or the like are received, it is difficult to present evaluations of other users on the basis of evaluations (‘like’, ‘cool’ or the like) for indicating preferences of users.
Further, in the methods disclosed in the Japanese Unexamined Patent Application Publication No. 2008-217311 and Japanese Unexamined Patent Application Publication No. 2008-217312, it is possible to recognize similar users, but it is difficult to specifically present how the similar users have evaluated predetermined items.
In addition, in the technology that users having similar value standards are presented from sentences on web pages, unless other users write sentences with respect to the same items as the present user, it is difficult to discriminate whether the other users have the similar value standards. Further, since similar discrimination is performed by only whether the evaluation is a positive evaluation or a negative evaluation, it is difficult to present detailed evaluation even in the case of similar users.
The present invention is contrived in consideration of the above problems, and particularly, provides details of preferences of other users in an easily recognized manner.